In maximum likleihood, we believe that the y-variable is conditionally normally distributed. So this means that errors are also normally distributed.
In ols regression, things seem to be more algebra/geometry driven. I am trying to fit a line of best fit between some points. I have done this in high school in my vector algebra class ... and there was never any mention of normal distribution in fitting a line of best fit.
So how come the errors in OLS are needed to be normally distributed?