Cluster sampling is a sampling method that divides a population into homogeneous groups called clusters, randomly selects some of these clusters, and collects data from the entire selected clusters. It has advantages such as being less time-consuming and costly than other methods while maintaining accurate data, as clusters are internally heterogeneous but externally homogeneous. Common cluster sampling methods include single-stage, multiple-stage, and two-stage cluster sampling.