1/ What is Unsupervised Learning?
A machine learning approach where models find patterns in unlabeled data without predefined outputs. It discovers hidden structures, clusters, or relationships. Key applications: clustering, anomaly detection, dimensionality reduction.

2/ How It Works
The model is trained on input-output pairs.
It identifies patterns and learns a function that generalizes to unseen data.
Performance is measured using metrics like accuracy, mean squared error, precision, and recall.