How are KNN and K-means clustering different?

KNN is a supervised learning algorithm, first and foremost. This algorithm needs tagged data to be trained. An unsupervised learning system called K-means scans the data for innate patterns. The number of closest data points, K, is used in KNN. The K in K-means, on the other hand, defines the number of centroids.