Given a set of objects each of which is represented by a finite number of attributes or features and a clustering criterion that associates a value of utility to any classification, the objective of a clustering method is to identify that classification of the objects which optimizes the criterion. A new strategy to solve this problem is developed. The approach is, in essence, a modification of the reproductive plan, a type of adaptive procedure devised by Holland [2], which embodies many principles found in the adaptation of natural systems through evolution. The proposed approach differs from conventional methods in the sense that the search through the space of possible solutions proceeds in a parallel fashion.The adaptive clustering strategy requires the specification of methods for the generation of an initial population of classifications, the parent selection, the modifications and the replacement of current classifications with new ones. The effects of changing several of these features are investigated. Experimental results show that it is possible to devise clustering strategies based on the principles of adaptation in natural systems that are both effective and efficient.