Unsupervised learning is a type of machine learning where the algorithm is trained on unlabeled data. Unlike supervised learning, which involves a training set with input-output pairs, unsupervised learning works with data that has no predefined labels or categories. The goal is to find hidden patterns or intrinsic structures within the data.
