DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a popular clustering algorithm in the field of data mining and machine learning. Unlike other clustering methods, DBSCAN can find clusters of arbitrary shapes and is particularly effective in identifying outliers or noise in the data.