Final answer:
The term describing an environment where new data is used to automatically retrain predictive models is 'online learning' or 'incremental learning'. These systems are ideal for real-time data environments and continuously update the model for improved performance.
Step-by-step explanation:
The term used to describe an environment in which new data is automatically collected and utilized to retrain updated versions of a predictive model is online learning or incremental learning. In this type of setting, the predictive model updates continuously as new data becomes available, improving its accuracy and performance over time. This approach is in contrast to batch learning where a model is trained on a fixed dataset and requires manual retraining with new data.
Online learning systems are commonly found in dynamic environments with real-time data, such as recommender systems, financial market analysis, and adaptive websites. The models adapt to the changing patterns in data, making them versatile and highly relevant for applications where timely updates are crucial.