You can test your model on past elections

IE X% of the time my model predicted the right result in this particular election.

You can test weather forecasts on the weather in the past.

You can test your model on a sports game on past games.

We do this all the time in many fields. With different degrees of certainty (error bars are small or large).

The entire basis of machine learning and predictions people use in everyday life is based on this assumption

That shows that your predictions are well calibrated in the aggregate. There is no way to know whether any one particular prediction was accurate.