DBSCAN (Density-Based Spatial Clustering of Applications with Noise): This algorithm forms clusters based on the density of data points. It groups points that are closely packed together and marks points in low-density regions as outliers. DBSCAN can find clusters of any shape and is good at separating high-density clusters from noise in the data.