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In unsupervised learning, machine learning algorithms are used to examine and cluster unlabeled data sets.

In unsupervised learning, clustering is used. Clustering is an approach used in data mining that groups unlabeled data based on parallels and variances within the data set

Unsupervised algorithms are used to uncover hidden associations within the data sets or patterns within data sets that may go unnoticed without the assistance of humans.

One of the benefits of unsupervised learning is the decrease of complexity due to the large volumes of data needed to train the system and the need for human intervention to validate results.