Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters).
Association rule learning is a method for discovering interesting relations between variables in large databases.
So both, clustering and association rule mining (ARM), are in the field of unsupervised machine learning. Clustering is about the data points, ARM is about finding relationships between the attributes of those datapoints.
However, I wonder if there are more relationships. For example, given a clustering, can this enhance / simplify ARM or vice versa?