Clustering (data mining) is a fundamental task within data mining, knowledge management, and data-intensive computing that involves partitioning a set of data objects into groups, called clusters, such that objects within the same cluster are more similar to each other than to objects in other clusters. It is an unsupervised learning method used to discover inherent groupings, structures, or patterns in unlabeled data based on defined similarity or distance measures. The primary objective is to identify homogeneous subgroups, facilitating data summarization, pattern recognition, anomaly detection, and serving as a preprocessing step for other analytical tasks like predictive modeling.