Clustering is a process of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. It is an unsupervised learning technique used to discover natural groupings within data without predefined labels. Clustering is widely used in customer segmentation, market research, image analysis, and anomaly detection. Popular clustering algorithms include k-means, hierarchical clustering, DBSCAN, and Gaussian mixture models. The goal is to maximize intra-cluster similarity and minimize inter-cluster similarity to reveal meaningful patterns and insights from the data. Clustering helps uncover hidden structures in data, supporting better understanding and analysis.