Is it true that parameter C cannot be optimized for 'nu-svr' or is it an error?

Question

I am trying to optimize an SVR model within the mlr3 ecosystem with the kernlab package and I am getting the following error:

The parameter 'C' can only be set if the following condition is met 'type <U+2208> {eps-svr, eps-bsvr}'. Instead the current parameter value is: type=nu-svr.

I find it very weird that cost parameter C cannot be optimized for type 'nu-svr'.

This is a part of my code:

library(mlr3tuning)

learner_ksvm$param_set

search_space = ps(
  C = p_dbl(lower = 0.01, upper = 1),
  type = p_fct(levels = c("eps-svr", "nu-svr")),
  epsilon = p_dbl(lower = 0.01, upper = 1)
)

measure = msr("regr.rmse")

terminator = trm("evals", n_evals = 10)

instance = TuningInstanceSingleCrit$new(
  task = task_train_prerp,
  learner = learner_ksvm,
  resampling = rsmp_cv,
  measure = measure,
  search_space = search_space,
  terminator = terminator
)

tuner = tnr("random_search")

library(progressr)
handlers(global = TRUE)
handlers("rstudio")

tuner$optimize(instance)