If you develop personalization of user experience for your website or an app, contextual bandits can help you. Using contextual bandits, you can choose which content to display to the user, rank advertisements, optimize search results, select the best image to show on the page, and much more.
There are many names for this class of algorithms: contextual bandits, multi-world testing, associative bandits, learning with partial feedback, learning with bandit feedback, bandits with side information, multi-class classification with bandit feedback, associative reinforcement learning, one-step reinforcement learning.
Researchers approach the problem from two different angles. You can think about contextual bandits as an extension of multi-armed bandits, or as a simplified version of reinforcement learning.