In the era of the digital revolution, online shopping has developed into a remarkably simple and economical option for consumers to make purchases securely and conveniently from their homes. In order for the online merchant to optimize their profit, the online shopping platform must always display a list of potential products that customers may purchase. The recommender system kicks in at this point to assist in finding products that customers would like and recommend a list of product recommendations that match the customer's preferences. This paper reviews the recommender system technology in detail by reviewing the classification technique. Other than that, the related works will be reviewed to understand how each technique works, the strengths and limitations, the datasets and evaluation metrics employed.