Associative Rule Mining in machine learning tries to find some interesting relationship among the variables of a dataset.
It is used in Market Basket Analysis by big retailers to find the relationship between different items. For example, the items which are purchased together are kept together in a store like eggs, milk, curd etc.
Associative Rule Mining works on the concept of an if-else statement, such as if X then Y. The if element is called Antecedent and then statement is called Consequent.