Answer Posted / Amit Kumar Giri

KNN (k-Nearest Neighbors) is a supervised learning algorithm used for classification and regression, whereas K-means Clustering is an unsupervised learning algorithm used for grouping similar data points into clusters. In KNN, the class of a new point is determined by the majority vote of its k-nearest neighbors in the training set, while K-means assigns each point to the centroid (mean) of its nearest cluster.

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