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K-Means Clustering Algorithm is a center-based, iterative machine learning algorithm that partitions unlabeled (unsupervised) data points into K clusters based on their similarity. Each data point belongs to exactly one cluster; in this regard, it is a "hard" clustering technique. Unlike supervised learning, the K-Means algorithm does not require class labels and aims to discover the natural structure within the data. Basic Working Principle The K-Means algorithm forms clusters around a predefin