Conceptual Clustering is an important and active research area that aims to efficiently cluster and explain the data. It approaches provide descriptions that do not use a human comprehensible knowledge. Most conceptual clustering methods are capable of generating hierarchical category structures. It is closely related to formal concept analysis, decision tree learning, and mixture model learning. Conceptual Clustering is obviously closely related to data clustering; however, it is not only the inherent structure of the data that drives cluster formation, but also the Description language which is available to the learner.