There are several applications of unsupervised learning algorithms. Let's take a look at a few here:

• Clustering: These types of algorithms allow us to categorize the dataset into several similar groups, referred to as a cluster. Each cluster represents a group of similar points. 
• Association mining: These types of unsupervised learning algorithms allow us to find frequently occurring items in our dataset. 
• Anomaly detection: These types of unsupervised learning algorithms help us to determine unusual data points in any existing dataset. 
• Dimensionality reduction: These techniques are commonly used in data processing in order to reduce the number of features in a dataset. This is one of the most important tasks to perform in unsupervised learning.