A machine learning model is the result of applying an ML algorithm to training data during the model-building phase. It represents the learned patterns, relationships, and rules derived from the data. Once trained, the model can be used in production to analyze new data and generate predictions, classifications, or insights.
In natural language processing (NLP), for example, a model is used to process text and return outputs such as sentiment analysis, topic classification, or language translation, based on the patterns it has learned.