The correct answer is: A. supervised.
Linear regression is a supervised machine learning algorithm. This means that it is trained on a set of data that includes both the input variables and the desired output. The algorithm then learns to map the input variables to the output variables.
Supervised learning algorithms are used in a wide variety of applications, including spam filtering, fraud detection, and medical diagnosis.
Unsupervised learning algorithms are used when there is no labeled data available. These algorithms can be used to find patterns in data, such as clusters or outliers.
Semi-supervised learning algorithms are used when there is a small amount of labeled data available. These algorithms can be used to improve the performance of supervised learning algorithms.
I hope this helps!