Unsupervised learning enables machine learning algorithms to discover patterns within data without pre-existing labels. Unlike supervised learning, which uses known answers for training, unsupervised methods explore data to find hidden structures such as customer segments, anomalies, or natural groupings. This is particularly valuable for real-world datasets that are not always neatly organized or labeled.
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