Image segmentation is the process of partitioning an image into multiple different regions (or segments). The goal is to change the representation of the image into an easier and more meaningful image.

K-Means clustering is unsupervised machine learning algorithm that aims to partition N observations into K clusters in which each observation belongs to the cluster with the nearest mean. A cluster refers to a collection of data points aggregated together because of certain similarities. For image segmentation, clusters here are different image colors.