diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
index 7111d54d65815..1da61d4b83e16 100644
--- a/doc/source/whatsnew/v1.2.0.rst
+++ b/doc/source/whatsnew/v1.2.0.rst
@@ -562,6 +562,7 @@ Other
 - Bug in :meth:`Index.union` behaving differently depending on whether operand is a :class:`Index` or other list-like (:issue:`36384`)
 - Passing an array with 2 or more dimensions to the :class:`Series` constructor now raises the more specific ``ValueError``, from a bare ``Exception`` previously (:issue:`35744`)
 - Bug in ``accessor.DirNamesMixin``, where ``dir(obj)`` wouldn't show attributes defined on the instance (:issue:`37173`).
+- Bug in :meth:`Series.nunique` with ``dropna=True`` was returning incorrect results when both ``NA`` and ``None`` missing values were present (:issue:`37566`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/base.py b/pandas/core/base.py
index c91e4db004f2a..8db1d8073fb7d 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -33,7 +33,7 @@
     is_scalar,
 )
 from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
-from pandas.core.dtypes.missing import isna
+from pandas.core.dtypes.missing import isna, remove_na_arraylike
 
 from pandas.core import algorithms
 from pandas.core.accessor import DirNamesMixin
@@ -1032,11 +1032,8 @@ def nunique(self, dropna: bool = True) -> int:
         >>> s.nunique()
         4
         """
-        uniqs = self.unique()
-        n = len(uniqs)
-        if dropna and isna(uniqs).any():
-            n -= 1
-        return n
+        obj = remove_na_arraylike(self) if dropna else self
+        return len(obj.unique())
 
     @property
     def is_unique(self) -> bool:
diff --git a/pandas/tests/base/test_unique.py b/pandas/tests/base/test_unique.py
index e5592cef59592..1a554c85e018b 100644
--- a/pandas/tests/base/test_unique.py
+++ b/pandas/tests/base/test_unique.py
@@ -121,3 +121,11 @@ def test_unique_bad_unicode(idx_or_series_w_bad_unicode):
     else:
         expected = np.array(["\ud83d"], dtype=object)
         tm.assert_numpy_array_equal(result, expected)
+
+
+@pytest.mark.parametrize("dropna", [True, False])
+def test_nunique_dropna(dropna):
+    # GH37566
+    s = pd.Series(["yes", "yes", pd.NA, np.nan, None, pd.NaT])
+    res = s.nunique(dropna)
+    assert res == 1 if dropna else 5