A Self-Organizing Map (SOM) is a type of artificial neural network used for unsupervised learning. It helps to visualize and cluster high-dimensional data by mapping it onto a lower-dimensional grid, usually a two-dimensional space. This process allows similar data points to be grouped together, making it easier to identify patterns and relationships within the data. SOMs are particularly useful in fields like data mining, image processing, and bioinformatics. By organizing complex data into a simpler format, they enable researchers and analysts to gain insights and make informed decisions based on the underlying structure of the data.