Clustering algorithms operate by analyzing a dataset and assigning data points to specific clusters based on their similarities. For instance, in a customer database, clustering can group customers based on purchasing behavior, demographics, or other relevant features. Popular clustering algorithms include K-means, Hierarchical Clustering, and DBSCAN.