Stemming algorithms are techniques used in natural language processing to reduce words to their base or root form. For example, the words "running," "runner," and "ran" can all be reduced to the root word "run." This process helps in improving the efficiency of text analysis by grouping similar words together, making it easier to search and analyze large datasets. Common stemming algorithms include the Porter Stemmer and the Snowball Stemmer. These algorithms use specific rules to strip suffixes from words, allowing for better matching in tasks like information retrieval and text mining. By simplifying words, stemming enhances the performance of various language processing applications.