Meaning of 'Closed Form'

Here's an excerpt from a paper explaining Logistic Regression. What does 'Closed Form' mean in this context? Please explain in simple terms. The definitions online are confusing.

Gradient of Log Likelihood: Now that we have a function for log-likelihood, we simply need to choose the values of theta that maximize it. Unfortunately, if we try just setting the derivative equal to zero, we’ll quickly get frustrated: there’s no closed form for the maximum. However, we can find the best values of theta by using an optimization algorithm. The optimization algorithm we will use requires the partial derivative of log likelihood with respect to each parameter.