* Firstly, KNN is a supervised learning algorithm. In order to train this algorithm, we require labeled data.
* K-means is an unsupervised learning algorithm that looks for patterns that are intrinsic to the data.
* The K in KNN is the number of nearest data points. On the contrary, the K in K-means specify the number of centroids.
