There are two main techniques used in machine learning:
Association: Association rule finds useful associations and relationships among large sets of data items. This rule shows how frequently a itemset occurs in a transaction. A typical example is a Market Based Analysis.
Clustering: Clustering is the task of dividing the data points into a number of groups such that the data points in the same groups are similar. It is basically a collection of objects on the basis of similarity and dissimilarity between them.