What happens when you have highly correlated columns in a dataset? I am doing a regression model. And I was wondering what would be the consequence if we have two or more Highly correlated columns in the dataset? Is that something that can decrease the accuracy of the model?
Answering this question would help decide how to deal with it. Would PCA be the best option here?
Having highly correlated features is a type of redundancy in features. And yes, it effects a regression model if you are having highly correlated features. A very nice explanation is given here. 

PCA is a nice choice when it comes to dimensionality reduction.