The Residual Nobody Wrote Down

An ordinary least-squares line fitted with an intercept is used to model $n = 6$ observations.

A colleague reports only five of the six residuals:

$2.0,\quad -1.5,\quad 0.5,\quad -1.0,\quad 1.5$

The sixth residual was lost, and the raw data are no longer available.

The Mean Squared Error averages the squared residuals over all $n$ observations:

$\text{MSE} = \frac{1}{n}\sum_{i=1}^{n}(y_i - \hat{y}_i)^2$

What is the Mean Squared Error of this fit?