I feel that since the question is asking for the most _accurate_ model, the justification for not picking kNN is wrong. Depending on the difficulty of the data, a linear model might underfit heavily, while kNN will probably have at least decent performance. The question does talk about “2 years worth of data”, but this might be just a few hundred measurements in the end – as long as nothing more is specified I wouldn’t automatically assume that there is too much training data for a non-parametric model (and even then you could use clustering and only using cluster means for kNN to reduce the number of data points used in kNN)
My objective when I wrote this question was to differentiate LR from KNN.
I think that the question still lacks information (e.g., characteristic of the training data, which one performs faster in giving predictions) to support the correct option. We will modify the scenario so it’ll have a clear distinction between kNN and Linear Learner.