Cluster analysis is a family of classification techniques for finding groups in data when both the number of groups, and which object falls in which group, are not observed at the start. The object is typically a case (data row), although it can be a variable. This makes cluster analysis a type of unsupervised learning, meaning that the data consists of inputs with no target variable. Since you are not aiming to predict or explain a target variable, you cannot turn to measures of model performance used in predictive modeling, such as classification accuracy or percent of variance explained.
Some researchers have contended that the idea of a cluster is ill-defined. However, most sources suggest that clusters are groupings of objects that can be understood in terms of internal cohesion (homogeneity) and external separation. Cluster analysis has been used in market research...