Ants, bees and other social insects deposit pheromone (a type of chemical) in order to communicate between the members of their community. Pheromone that causes clumping or clustering behavior in a species and brings individuals into a closer proximity is called aggregation pheromone. This paper presents a new algorithm (called APC) for clustering data set based on this property of aggregation pheromone found in ants. At each location of data point an ant is placed, and the ants are allowed to move in the search space to find points with higher pheromone density. The movement of an ant is governed by the amount of pheromone deposited at different points of the search space. If the pheromone density is more at a point, more ants are attracted towards this point. This leads to the formation of homogenous groups of data. The proposed algorithm is evaluated on a number of well-known benchmark data sets using different cluster validity measures. Results are compared with those obtained using average linkage clustering algorithm and are found to be better and robust.